Papers with Code 아카이브

Small Data Image Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 12
보존된 평가 기록: 47

Supervised image classification with tens to hundreds of labeled training examples.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AmalRT/DNN_Reg

공식 코드

Stochastic Function Norm Regularization of Deep Networks

https://github.com/AvivNavon/AuxiLearn

공식 코드

Auxiliary Learning by Implicit Differentiation

https://github.com/DSPsleeporg/smiles-transformer

공식 코드

SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery

https://github.com/DmitriiShubin/Variance-Aware-Training

공식 코드

About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations

https://github.com/EIDOSlab/unveiling-covid19-from-cxr

공식 코드

Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data

https://github.com/IdanAzuri/glico-learning-small-sample

공식 코드

Generative Latent Implicit Conditional Optimization when Learning from Small Sample

https://github.com/IdeasLabUT/EDA-Artifact-Detection

공식 코드

Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity Data

https://github.com/LeoYu/neural-tangent-kernel-UCI

공식 코드

Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

https://github.com/OE-FET/FraGVAE

공식 코드

Fragment Graphical Variational AutoEncoding for Screening Molecules with Small Data

https://github.com/PhIMaL/DeePyMoD

공식 코드

DeepMoD: Deep learning for Model Discovery in noisy data

https://github.com/SebastianKaltenbach/PhysicalConstraints_ProbabilisticCG

공식 코드

Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems

https://github.com/UKPLab/tacl2020-interactive-ranking

공식 코드

Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation

https://github.com/VisaoComputacional/mira

공식 코드

MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems

https://github.com/YuntianChen/EnLSTM

공식 코드

Ensemble long short-term memory (EnLSTM) network

https://github.com/alinlab/L2T-ww

공식 코드

Learning What and Where to Transfer

https://github.com/ankurmallick/dpkl

공식 코드

Deep Kernels with Probabilistic Embeddings for Small-Data Learning

https://github.com/aramis-lab/AD-ML

공식 코드

Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease

https://github.com/arjish/meta-meta-classification

공식 코드

Meta-Meta Classification for One-Shot Learning

https://github.com/bentherien/ParametricScatteringNetworks

공식 코드

Parametric Scattering Networks

https://github.com/cics-nd/pde-surrogate

공식 코드

Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data

https://github.com/congriUQ/physics_aware_surrogate

공식 코드

A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime

https://github.com/creinders/chimeramix

공식 코드

ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing

https://github.com/cumf/cumf_sgd

공식 코드

CuMF_SGD: Fast and Scalable Matrix Factorization

https://github.com/cvjena/deic

공식 코드

Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification

https://github.com/emaasit/long-range-extrapolation

공식 코드

Capturing Structure Implicitly from Time-Series having Limited Data

https://github.com/fgnt/pb_chime5

공식 코드

Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR

https://github.com/idelbrid/Randomly-Projected-Additive-GPs

공식 코드

Randomly Projected Additive Gaussian Processes for Regression

https://github.com/ieee8023/covid-chestxray-dataset

공식 코드

Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data

https://github.com/jlezama/OrthogonalLowrankEmbedding

공식 코드

OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning

https://github.com/kinredon/umt

공식 코드

Unbiased Mean Teacher for Cross-domain Object Detection

https://github.com/maziarraissi/HPM

공식 코드

Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations

https://github.com/minimalparts/nonce2vec

공식 코드

High-risk learning: acquiring new word vectors from tiny data

https://github.com/mlmed/torchxrayvision

공식 코드

TorchXRayVision: A library of chest X-ray datasets and models

https://github.com/msahamed/earthquake_physics_bayesian_nn

공식 코드

Estimating uncertainty of earthquake rupture using Bayesian neural network

https://github.com/muradtuk/SVMCoreset

공식 코드

On Coresets for Support Vector Machines

https://github.com/oskyhn/CNNs-Without-Borders

공식 코드

On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.